Trends in Analytical Chemistry最新文献_第6页

Cutting-edge progress in carbon nanomaterial-functionalized silver nanoparticles for enhanced optical and electrochemical sensing applications 用于增强光学和电化学传感应用的碳纳米材料功能化银纳米粒子的前沿进展

IF 11.8 1区化学

Trends in Analytical Chemistry Pub Date : 2024-10-01 DOI: 10.1016/j.trac.2024.117995

Rehab H. Elattar , Galal Magdy , Randa A. Abdel Salam , Ghada M. Hadad , Asmaa Kamal El-Deen

{"title":"Cutting-edge progress in carbon nanomaterial-functionalized silver nanoparticles for enhanced optical and electrochemical sensing applications","authors":"Rehab H. Elattar , Galal Magdy , Randa A. Abdel Salam , Ghada M. Hadad , Asmaa Kamal El-Deen","doi":"10.1016/j.trac.2024.117995","DOIUrl":"10.1016/j.trac.2024.117995","url":null,"abstract":"<div><div>Carbon nanomaterials and metal nanoparticles have garnered significant attention in many different fields due to their low toxicity, photo/chemical stability, biocompatibility, tunability, and outstanding optical properties. Recently, the functionalization of silver nanoparticles with carbon nanomaterials (CNMs/AgNPs) has emerged as a promising approach for enhancing sensing applications owing to the acquisition of new properties, such as physicochemical, mechanical, electrical, and optical characteristics. This review article provides an overview of the various types, synthesis methods, and characterization techniques of CNMs/AgNPs, and outlines the advantages, limitations, and diverse sensing applications of these nanocomposites. It also delves into the variety of employed sensing mechanisms, such as electrochemical modulation, fluorescence enhancement or quenching, and surface plasmon resonance. Additionally, future perspectives and emerging trends in CNMs/AgNPs are discussed. This review is expected to serve as a valuable reference for researchers and scientists interested in exploring the potential of CNMs/AgNPs for advanced sensing applications.</div></div>","PeriodicalId":439,"journal":{"name":"Trends in Analytical Chemistry","volume":"181 ","pages":"Article 117995"},"PeriodicalIF":11.8,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142427754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Infrared and Raman spectroscopy in conjunction with chemometric methods in questioned document analysis: Forensic applications 红外光谱和拉曼光谱与化学计量学方法在可疑文件分析中的结合：法医应用

IF 11.8 1区化学

Trends in Analytical Chemistry Pub Date : 2024-09-26 DOI: 10.1016/j.trac.2024.117989

Vishal Sharma , Romika Chopra , Neha Verma , Pawan Kumar Mishra , Rafał Cieśla

{"title":"Infrared and Raman spectroscopy in conjunction with chemometric methods in questioned document analysis: Forensic applications","authors":"Vishal Sharma , Romika Chopra , Neha Verma , Pawan Kumar Mishra , Rafał Cieśla","doi":"10.1016/j.trac.2024.117989","DOIUrl":"10.1016/j.trac.2024.117989","url":null,"abstract":"<div><div>The manipulation of documents remains a common tool for fraudulent activities, encompassing disputed signatures, threatening letters, counterfeit currency, false medical documents, cloned cheques, and forged security documents. With technological advancements, document creation has evolved from manual handwriting to computer-generated formats, employing various devices such as printers, photocopiers, scanners, and multifunctional devices globally. Forensic document examiners grapple with these challenges, and ongoing efforts are dedicated to addressing them. This study provides a comprehensive review of publications from the past decade, focusing on dating studies, ink and paper analysis, examination of writing and printing inks, ink analysis of questioned documents, and research on intersecting lines. The central emphasis lies on the utilization of Infrared and Raman spectroscopy within the domain of Vibrational spectroscopy. The review also highlights current trends, major challenges, and the effective application of chemometric approaches in this field.</div></div>","PeriodicalId":439,"journal":{"name":"Trends in Analytical Chemistry","volume":"180 ","pages":"Article 117989"},"PeriodicalIF":11.8,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142418082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Use of living systems for clinical diagnostics by monitoring volatile chemicals 通过监测挥发性化学物质将生物系统用于临床诊断

IF 11.8 1区化学

Trends in Analytical Chemistry Pub Date : 2024-09-26 DOI: 10.1016/j.trac.2024.117987

Autumn K. McLane-Svoboda , Simon W. Sanchez , Michael Parnas , Ehsanul Hoque Apu , Debajit Saha

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Preface to the special issue: Disinfection byproducts 特刊序言：消毒副产品

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Trends in Analytical Chemistry Pub Date : 2024-09-25 DOI: 10.1016/j.trac.2024.117982

Patricia Forbes

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Molecular characterization of atmospheric organic aerosols: Contemporary applications of high-resolution mass spectrometry 大气有机气溶胶的分子特征：高分辨率质谱仪的当代应用

IF 11.8 1区化学

Trends in Analytical Chemistry Pub Date : 2024-09-25 DOI: 10.1016/j.trac.2024.117986

Qiaorong Xie, Alexander Laskin

{"title":"Molecular characterization of atmospheric organic aerosols: Contemporary applications of high-resolution mass spectrometry","authors":"Qiaorong Xie, Alexander Laskin","doi":"10.1016/j.trac.2024.117986","DOIUrl":"10.1016/j.trac.2024.117986","url":null,"abstract":"<div><div>Recent advances in the molecular characterization of atmospheric organic aerosols by high-resolution mass spectrometry (HRMS) have significantly enhanced our understanding of atmospheric chemistry and its environmental implications. This perspective review manuscript showcases the contemporary applications of HRMS methodologies in both field and laboratory studies of organic aerosols. Structured into three sections, the review begins with investigations utilizing ultrahigh mass resolving power to explore the precursors and formation mechanisms of organosulfur, organophosphorus, and other multifunctional species within organic aerosol mixtures. The second section discusses novel applications for understanding the atmospheric chemistry of brown carbon, facilitating the classification of brown carbon chromophores and quantifying their contributions to light absorption. The third section highlights studies on the gas-particle partitioning of organic aerosol components, examining their composition and viscosity. The manuscript concludes by discussing future research directions in this field, highlighting ongoing advancements and potential areas for further exploration.</div></div>","PeriodicalId":439,"journal":{"name":"Trends in Analytical Chemistry","volume":"181 ","pages":"Article 117986"},"PeriodicalIF":11.8,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142427171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Machine learning-assisted identification of environmental pollutants by liquid chromatography coupled with high-resolution mass spectrometry 液相色谱-高分辨质谱法在机器学习辅助下识别环境污染物

IF 11.8 1区化学

Trends in Analytical Chemistry Pub Date : 2024-09-25 DOI: 10.1016/j.trac.2024.117988

Haotian Wang , Laijin Zhong , Wenyuan Su , Ting Ruan , Guibin Jiang

{"title":"Machine learning-assisted identification of environmental pollutants by liquid chromatography coupled with high-resolution mass spectrometry","authors":"Haotian Wang , Laijin Zhong , Wenyuan Su , Ting Ruan , Guibin Jiang","doi":"10.1016/j.trac.2024.117988","DOIUrl":"10.1016/j.trac.2024.117988","url":null,"abstract":"<div><div>Chemical exposure can be linked with various adverse effects, but the causal association is still poorly understood. To meet the challenge, non-target screening (NTS) based on liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) is increasingly applied to identify known and unknown chemicals with toxicological concerns present in environmental and biological samples. In this review, we highlight that the integration of predictive toxicology in NTS workflows enables large-scale screening for emerging chemical contaminants. We summarize the applications of machine learning (ML) and deep learning (DL) in toxicity prediction with a focus on biological pathway perturbation and LC-HRMS data processing, especially in peak picking and molecular structure elucidation. The substantial progress in computational approaches allows for identifying and prioritizing emerging chemical contaminants with improved accuracy, reproducibility, and efficacy. ML and DL will become next-generation informatics tools in NTS workflows to better characterize exposure to environmental pollutants.</div></div>","PeriodicalId":439,"journal":{"name":"Trends in Analytical Chemistry","volume":"180 ","pages":"Article 117988"},"PeriodicalIF":11.8,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142418145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Nanoparticle-driven biosensors for diagnosis of viral hepatitis 用于诊断病毒性肝炎的纳米粒子驱动生物传感器

IF 11.8 1区化学

Trends in Analytical Chemistry Pub Date : 2024-09-24 DOI: 10.1016/j.trac.2024.117985

Chenggong Zhu , Zhen Xun , Ruijie Fu , Qunfang Huang , Qishui Ou , Yunlei Xianyu , Can Liu

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Advances in the recognition strategies and analytical techniques of bile acids 胆汁酸识别策略和分析技术的进展

IF 11.8 1区化学

Trends in Analytical Chemistry Pub Date : 2024-09-23 DOI: 10.1016/j.trac.2024.117984

Xiaoyun Hu , Chen Liu , Jialing Zhou , Wei Li , Zhihui Dai

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Intermolecular forces and assembly strategies in porphyrin-based electrochemiluminescence: Mechanisms and future prospects 基于卟啉的电化学发光中的分子间作用力和组装策略：机理与未来展望

IF 11.8 1区化学

Trends in Analytical Chemistry Pub Date : 2024-09-21 DOI: 10.1016/j.trac.2024.117969

Yi-Xuan Li , Yu-Xuan Dai , Jérôme Chauvin , Xue-Ji Zhang , Serge Cosnier , Dan Shan

{"title":"Intermolecular forces and assembly strategies in porphyrin-based electrochemiluminescence: Mechanisms and future prospects","authors":"Yi-Xuan Li , Yu-Xuan Dai , Jérôme Chauvin , Xue-Ji Zhang , Serge Cosnier , Dan Shan","doi":"10.1016/j.trac.2024.117969","DOIUrl":"10.1016/j.trac.2024.117969","url":null,"abstract":"<div><div>The exploration of innovative luminophores is critical for enhancing the efficiency and stability of electrochemiluminescence (ECL). Porphyrins, with their superior optical and electrical properties, have emerged as promising organic ECL emitters. The tunable functional groups of the porphyrins facilitate their assembly into ordered structures, thereby reducing aggregation-caused quenching (ACQ) and achieving desirable photophysical properties. This review introduces the effect of central metal and peripheral substituents of porphyrins on their ECL properties. It then summarizes various assembly strategies for developing enhanced porphyrin-based ECL emitters, focusing on the intermolecular forces introduced by the porphyrin ring, the central metal and peripheral substituents. By correlating characterization and ECL results, the structure-activity relationship between porphyrin assembly structure and ECL performance is analyzed, providing significant reference and guidance for the future design of organic ECL emitters. Finally, current challenges and future perspectives for the construction of porphyrin-based ECL emitters are discussed.</div></div>","PeriodicalId":439,"journal":{"name":"Trends in Analytical Chemistry","volume":"180 ","pages":"Article 117969"},"PeriodicalIF":11.8,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142315845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Machine learning approaches for monitoring environmental metal pollutants: Recent advances in source apportionment, detection, quantification, and risk assessment 监测环境金属污染物的机器学习方法：来源分配、检测、量化和风险评估方面的最新进展

IF 11.8 1区化学

Trends in Analytical Chemistry Pub Date : 2024-09-21 DOI: 10.1016/j.trac.2024.117980

François Nkinahamira , Anqi Feng , Lijie Zhang , Hongwei Rong , Pamphile Ndagijimana , Dabin Guo , Baihui Cui , Huichun Zhang

{"title":"Machine learning approaches for monitoring environmental metal pollutants: Recent advances in source apportionment, detection, quantification, and risk assessment","authors":"François Nkinahamira , Anqi Feng , Lijie Zhang , Hongwei Rong , Pamphile Ndagijimana , Dabin Guo , Baihui Cui , Huichun Zhang","doi":"10.1016/j.trac.2024.117980","DOIUrl":"10.1016/j.trac.2024.117980","url":null,"abstract":"<div><div>Metal pollutants pose significant and enduring threats to human health and the environment, mainly due to their non-biodegradable nature. Traditional monitoring of these pollutants involves costly and time-consuming analytical methods. However, this conventional approach struggles to grasp the intricate and nonlinear connections between metals and the factors affecting pollution dynamics. Machine learning (ML) has emerged as a promising solution, capable of handling large datasets, diverse inputs, and complex patterns. This review highlights insights from developing innovative ML models to monitor metal pollutants. Beginning with an overview of commonly used ML algorithms for this purpose, the review comprehensively explores recent advancements in ML applications across various environmental matrices. It covers source apportionment, detection, quantification, and ecological risk assessment in solids, water, and air. The review also identifies research gaps and proposes future directions for maximizing ML's potential in preventing and managing environmental metal pollution.</div></div>","PeriodicalId":439,"journal":{"name":"Trends in Analytical Chemistry","volume":"180 ","pages":"Article 117980"},"PeriodicalIF":11.8,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142319541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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